Scaling up WA* with commitment and diversity

Authors:
David Furcy;Sven Koenig
Affiliations:
University of Wisconsin Oshkosh, Computer Science Department, Oshkosh, WI;University of Southern California, Computer Science Department, Los Angeles, CA
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

Citing 2
Cited 1

KBFS: K-Best-First Search

Annals of Mathematics and Artificial Intelligence
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Speeding up the convergence of online heuristic search and scaling up offline heuristic search

Limited discrepancy beam search

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence

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Abstract

Weighted A* (WA*) is a popular search technique that scales up A* while sacrificing solution quality. Recently, researchers have proposed two variants of WA*: KWA* adds diversity to WA*, and MSC-WA* adds commitment to WA*. In this paper, we demonstrate that there is benefit in combining them. The resulting MSC-KWA* scales up to larger domains than WA*, KWA* and MSC-WA*, which is rather surprising since diversity and commitment at first glance seem to be opposing concepts.